In this paper, an adaptive neural fault-tolerant control scheme is proposed for the three degrees of freedom model helicopter, subject to system uncertainties, unknown external disturbances, and actuator faults. To tackle uncertainty nonlinear faults, a network disturbance observer developed based on radial basis function network. The approximation errors are treated as compound that estimated by another observer. A observer-based then track desired output in presence uncertainty,...

This paper investigates the problem of event-triggered H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control for a networked singular system with both state and input subject to quantizations. First, discrete scheme, which activates only at each sampling instance, is presented. Next, two new sector bound conditions quantizers are proposed provide more intuitive stability analysis controller design. Then, network conditions,...

This paper investigates the problem of exponential passive filtering for a class stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate states by designing Luenberger-type observer, such that filter error dynamics are mean-square exponentially stable an expected decay rate attenuation level. Sufficient conditions existence filters obtained, convex optimization algorithm design given. In addition, cone complementarity...

In this note, a robust constrained control scheme is proposed for multi-input and multi-output (MIMO) cascade nonlinear systems with unknown external disturbance input saturation. To efficiently observe disturbance, novel sliding mode observer (SMDO) finite time convergence performance presented. A developed MIMO based on backstepping techniques the estimate of SMDO. With first-order differentiator introduced to compute derivatives virtual laws, computational burden in reduced system....

This paper investigates the problem of fault detection filter design for nonhomogeneous Markovian jump systems by a Takagi-Sugeno fuzzy approach. Attention is focused on construction to ensure estimation error dynamic stochastically stable, and prescribed performance requirement can be satisfied. The designed model-based guarantee sensitivity residual signal faults robustness external disturbances. By using cone complementarity linearization algorithm, existence conditions filters are...

This paper studies the problem of event-triggered fault detection filter (FDF) and controller coordinated design for a continuous-time networked control system (NCS) with biased sensor faults. By considering sensor-to-FDF network-induced delays packet dropouts, which do not impose constraint on event-triggering mechanism, proposing simultaneous network bandwidth utilization ratio occurrence probability-based new closed-loop model considered NCS is established. Based established model, H ∞...

This paper is concerned with the quantized control design problem for a class of semi-Markovian jump systems repeated scalar nonlinearities. A system this kind has been transformed into an associated Markovian via supplementary variable technique and plant transformation. sufficient condition developed. guarantees that corresponding closed-loop are stochastically stable have prescribed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub>...

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account occurrence progress and probability, introducing an parameter, novel mechanism is proposed achieve efficient utilization communication network bandwidth. Both sensor-to-control station station-to-actuator network-induced delays are taken account. The event-triggered sensor...

This article addresses the problem of lateral control for networked-based autonomous vehicle systems. A novel solution is presented nonlinear vehicles to smoothly follow planned path under external disturbances and network-induced issues, such as cyber-attacks, time delays, limited bandwidths. First, a fuzzy-model-based system established represent networked systems subject hybrid cyber-attacks. To reduce network burden effects an asynchronous resilient event-triggered scheme (ETS) proposed....

In this paper, the problem of adaptive active fault-tolerant control for a class nonlinear systems with unknown actuator fault is investigated. The assumed to have no traditional affine appearance system state variables and input. useful property basis function radial neural network (NN), which will be used in design tolerant controller, explored. Based on analysis normal passive controllers, by using implicit theorem, novel NN-based scheme alarm proposed. Comparing results literature, can...

Summary The problem of H ∞ control for networked Markovian jump system under event‐triggered scheme is studied in this paper. In order to reduce the utilization limited network bandwidth, a dynamic discrete choose transmitted data designed. A time‐delay model employed describe and related behavior, such as transmission delay, package dropout, disorder. Furthermore, sufficient condition derived guarantee that resulting closed‐loop stable has prescribed performance index. co‐design method...

In this paper, we investigate the adaptive exponential synchronization in both mean square and almost sure senses for an array of N identical Markovian stochastic coupled neural networks neutral-type with time-varying delay random coupling strength. The generalized Lyapunov theorem stability neutral Markov system is first established. assumed to be a bounded measurable function. Then, sufficient conditions guarantee underlying are developed under feedback controller, which given terms...

This paper addresses the problem of robust fuzzy L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> - xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> filtering for a class uncertain nonlinear discrete-time Markov jump systems (MJSs) with nonhomogeneous processes. The Takagi-Sugeno model is employed to represent such MJS norm-bounded parameter uncertainties. In order decrease conservation, polytope Lyapunov function which evolves as...

This paper focuses on the problem of adaptive output-constrained neural tracking control for uncertain nonstrict-feedback systems in presence unknown symmetric output dead zone and input saturation. A Nussbaum-type function-based dead-zone model is introduced such that dynamic surface approach can be used controller design. The variable separation technique employed to decompose function entire states each subsystem into a series smooth functions. Radial basis networks are utilized...

This paper proposes a new adaptive controller for class of uncertain nonlinear systems with quantized signal. Fuzzy logic are utilized to approximate terms without imposing prior matching conditions required. A hysteretic type quantizer is incorporated reduce chattering. backstepping designed guarantee that the underlying system semiglobally uniformly ultimately bounded. Two numerical examples presented demonstrate effectiveness and potential proposed techniques.

In this article, a distributed adaptive event-triggered formation control strategy is proposed for unified nonlinear heterogeneous multiagent systems under uncertainties and disturbances to achieve time-varying formations. To reduce the frequency of data transmission, dual observer with an developed estimate states reference exosystem. Without incurring prior global information about communication graph, novel robust controller, dynamic compensators disturbances, designed based on result...

In this paper, the exponential stability in p th( > 1 )-moment for neutral stochastic Markov systems with time-varying delay is studied. The derived conditions comprise two forms: 1) delay-independent criteria which are obtained by establishing an integral inequality and 2) delay-dependent captured using theory of functional differential equations. As its applications, results used to investigate neural networks switching, globally adaptive synchronization complex dynamical respectively. On...

This paper is concerned with the problem of adaptive neural tracking control for a class uncertain pure-feedback nonlinear systems. Using implicit function theorem and backstepping technique, practical robust scheme proposed to guarantee that error converges an adjusted neighborhood origin by choosing appropriate design parameters. In contrast conventional Lyapunov-based techniques, alternative Lyapunov constructed development law learning algorithms. Differing from existing results in...

In this study, a theoretical framework for reconfigurable flight control is developed and applied to near space vehicle (NSV) attitude dynamics. First, NSV reentry mode described. Second, an adaptive neural network observer proposed, which ensures asymptotic convergence of the state error zero under effector damage uncertainty. Next, command-filter backstepping controller designed based on observer. The authors focus accommodation damage, uncertainty resulting disturbances. It shown that...

This article proposes, a novel obstacle avoidance algorithm for mobile robot based on finite memory filtering (FMF) in unknown dynamic environments. To overcome the limitations of existing window approach (DWA), we propose new version DWA, called distribution estimation-based (FDEDWA), which is an that avoids obstacles through estimating overall obstacles. FDEDWA estimates FMF, and predicts future The FMF derived to minimize effect measurement noise Frobenius norm, covariance matrix...